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1. Algorithmic Trading: What Is It and How Does It Work? Algorithmic trading is a type of trading that uses complex algorithms to determine the best time to buy or sell a stock or other financial instrument. Algorithmic trading systems use mathematical models and computer programs to make decisions about when to buy and sell. These systems can scan markets for potential opportunities, monitor news and events, and execute trades according to predetermined rules. Algorithmic trading has become increasingly popular as technology and computing power have advanced, making it possible to execute trades faster and with greater precision. Algorithmic trading can be used to help traders achieve better returns and reduce risk by eliminating emotions from the decision-making process.
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dbi Blog
Introduction SQL Server 2025 introduces a new algorithm for backup compression: ZSTD. As a result, SQL Server 2025 now offers three solutions for backup compression: In this blog, we will compare MS_XPRESS and ZSTD. Environment To perform these tests, the following virtual machine was used: Additionally, I used the StackOverflow database to run the backup […]
How to Evaluate LLMs and Algorithms — The Right Way | Towards Data Science
Never miss a new edition of The Variable, our weekly newsletter featuring a top-notch selection of editors’ picks, deep dives, community news, and more. Subscribe today! All the hard work it takes to integrate large language models and powerful algorithms into your workflows can go to waste if the outputs you see don’t live up to expectations. […]
Taylor Series Approximation To Newton Raphson Algorithm – A note for myself of the proof | R-bloggers
We learnt to derive the Newton-Raphson algorithm from Taylor series approximation and implements it for logistic regression in R. We’ll show how the second-order Taylor expansion leads to the Newton-Raphson update formula, then compare individua...
Tokenizers in Language Models - MachineLearningMastery.com
Tokenization is a crucial preprocessing step in natural language processing (NLP) that converts raw text into tokens that can be processed by language models. Modern language models use sophisticated tokenization algorithms to handle the complexity of human language. In this article, we will explore common tokenization algorithms used in modern LLMs, their implementation, and how to use them. Let's get…